Positive COVID-19 Research Articles

Comparison of the effectiveness of the quick COVID-19 severity index and the COVID-19 gram critical illness risk score in identifying critical patients with COVID-19

Objectives: This study aimed to compare the effectiveness of the Quick COVID-19 Severity Index (qCSI) and the COVID-GRAM Critical Illness Risk Score (CGCIRS) in identifying critically ill patients with COVID-19 admitted to the emergency department of a tertiary hospital. Methods: Patients over 18 years of age with a positive PCR test who presented to the Emergency Department of Bursa Yüksek İhtisas Training and Research Hospital between 15.03.2020 and 15.03.2021 with COVID-19 findings were retrospectively included in the study. Mortality, qCSI (respiratory rate per minute, oxygen saturation, oxygen demand per minute), and CGCIRS (x-ray abnormality, age, hemoptysis, dyspnea, impaired consciousness, comorbid disease, presence of cancer, neutrophil/lymphocyte ratio, lactate dehydrogenase (LDH) value, direct bilirubin value) were investigated within 1, 7 and 28 days. Results: A total of 1499 patients with a positive COVID-19 PCR test were included in the study. Invasive mechanical ventilation was performed in 44 (2.9%) and non-invasive mechanical ventilation in 63 (4.2%) patients. 57 (3.8%) patients were hospitalized in the intensive care unit (ICU). Mortality occurred in the first 24 hours in 1 (0.1%) and 28 days in 41 (2.7%) patients. Having comorbidities, use of 10 lt/min oxygen, use of high flow oxygen, need for non-invasive and invasive mechanical ventilation, and need for ICU were found to increase 28-day mortality significantly. The qCSI and CGCIRS were found to be significantly different in patients who developed 28-day mortality with qCSI and CGCIRS, respectively (p

Somatic, emotional, and gastrointestinal symptom severity are increased among children and adolescents with COVID-19.

Post-infectious disorders of gut-brain interaction (PI-DGBI) have significant impact on children and adolescents. The effect of COVID-19 on PI-DGBI-associated symptoms in this population, however, is unknown. We performed electronic medical record searches to identify patients 8-17 years old with a SARS-CoV2 PCR test at Lurie Children's Hospital between November 2020 and March 2021 (cohort 1) and April-October 2021 (cohort 2). Questionnaires were administered to assess symptoms prior to and 3 months following the test. This included the Pediatric Eosinophilic Esophagitis Symptom Score (PEESS), questionnaire of pediatric gastrointestinal symptoms-Rome IV, Nausea Profile (NP), dyspepsia symptom survey (DSS), nausea severity profile (NSP), and Pediatric Quality of Life Inventory (PedsQL). We grouped patients based on the presence of symptoms prior to COVID-19 test or the test result. One hundred and ninety-six parent(s) or guardian(s) in cohort 1 and 274 in cohort 2 completed surveys and self-reported their child's COVID-19 result. Cohort 1 had increased PEESS and DSS scores, lower PedsQL scores, and increased frequency of abdominal pain disorders among patients with symptoms prior to COVID-19 testing. Both cohorts had increased NP and NSP scores among patients with symptoms prior to COVID-19 testing that was highest among patients with a positive COVID-19 test. Abdominal pain and diarrhea prior to COVID-19 testing predicted higher NP scores. Among symptomatic COVID-19 tested children, we found increased severity of nausea-associated somatic, emotional, and gastrointestinal symptoms in the 3 months following the test that was most increased among patients with a positive COVID-19 test.

Detection of COVID-19 incidence among attendees of the 2022 Hajj season

ObjectivesThis study investigated the presence of COVID-19 cases among pilgrims, health care workers (HCWs), and non-HCWs of Hajj 2022. MethodsNasopharyngeal samples were collected from 491 attendees of Hajj 2022. All participants received three doses of COVID-19 vaccines. Paired (n = 138; 69 participants) and unpaired (n = 422; 422 participants) nasopharyngeal swabs were subjected to reverse transcription–polymerase chain reaction targeting E gene of β-coronaviruses and RNA-dependent RNA polymerase of SARS-CoV-2. The results were linked to the participants’ profiles, including role during Hajj, presence of respiratory symptoms or comorbidities, contact with symptomatic individuals, smoking status, and COVID-19 recovery. ResultsA total of 20 (20 of 560; 3.6%) samples tested positive for COVID-19. Most cases (18 of 20; 90%) were pilgrims and non-HCWs. Six (30%) samples belonged to participants with previous positive reverse transcription–polymerase chain reaction. A total of 12 (60%) samples belonged to participants with respiratory symptoms. Three (15%) cases were linked to participants who had contact with individuals with respiratory symptoms. All cases belonged to individuals with no comorbidities, apart from a single case who has a chronic sinusitis. Five (25%) cases were smokers. No significant association was found between positive COVID-19 test and participants’ profiles. ConclusionsFew COVID-19 cases were detected in this study. Sustainable surveillance of COVID-19 and other respiratory viruses during Hajj seasons remains necessary.

Patients with type 1 diabetes are at elevated risk of developing new hypertension, chronic kidney disease and diabetic ketoacidosis after COVID-19: Up to 40 months' follow-up.

The aim was to investigate whether COVID-19 increases new incidence of hypertension (HTN), chronic kidney disease (CKD) and diabetic ketoacidosis (DKA) in patients with type 1 diabetes (T1D) up to 40 months post-infection. Three groups of patients from the Montefiore Health System in the Bronx (1 March 2020 to 1 July 2023) were studied: T1D patients hospitalized for COVID-19 (H-COVID-19, n = 511), T1D patients with COVID-19 but not hospitalized for COVID-19 (NH-COVID-19, n = 306) and T1D patients without a positive COVID-19 test on record (non-COVID-19, n = 1547). COVID-19 patients were those with a positive polymerase-chain-reaction test on record, and non-COVID-19 patients were either tested negative or not tested on record. Cumulative incidences and adjusted hazard ratios (aHR) with 95% confidence intervals (CI) were computed with adjustment for competing risks. Compared to non-COVID-19 patients, both H-COVID-19 (unadjusted 19.72% vs. 3.14%, p < 0.001; aHR = 7.55 [3.33, 17.06], p < 0.001) and NH-COVID-19 (10.26% vs. 3.14%, p = 0.004; aHR = 5.08 [2.19, 11.78], p < 0.001) patients were more likely to develop new HTN. Compared to non-COVID-19 patients, both H-COVID-19 (11.41% vs. 1.14%, p < 0.001; aHR = 9.76 [4.248, 22.25], p < 0.001) and NH-COVID-19 (7.69% vs. 1.14%, p < 0.001; aHR = 6.54 [2.91, 14.67], p < 0.001) patients were more likely to develop new CKD. Compared to non-COVID-19 patients, both H-COVID-19 (4.09% vs. 1.06%, p < 0.001; aHR = 12.24 [4.09, 36.59], p < 0.001) and NH-COVID-19 (3.06% vs. 1.06%, p = 0.035; aHR = 12.94 [4.09, 40.89], p < 0.001) patients were more likely to develop new DKA at follow-up. T1D patients with COVID-19 are at higher risk of developing new HTN, CKD and DKA compared to T1D patients without COVID-19.

COVID-19 Computed tomography patterns in renal replacement therapy patients.

Lung diseases are common in patients with end stage kidney disease (ESKD), making differential diagnosis with COVID-19 a challenge. This study describes pulmonary chest tomography (CT) findings in hospitalized ESKD patients on renal replacement therapy (RRT) with clinical suspicion of COVID-19. ESKD individuals referred to emergency department older than 18 years with clinical suspicion of COVID-19 were recruited. Epidemiological baseline clinical information was extracted from electronic health records. Pulmonary CT was classified as typical, indeterminate, atypical or negative. We then compared the CT findings of positive and negative COVID-19 patients. We recruited 109 patients (62.3% COVID-19-positive) between March and December 2020, mean age 60 ± 12.5 years, 43% female. The most common etiology of ESKD was diabetes. Median time on dialysis was 36 months, interquartile range = 12-84. The most common pulmonary lesion on CT was ground glass opacities. Typical CT pattern was more common in COVID-19 patients (40 (61%) vs 0 (0%) in non-COVID-19 patients, p < 0.001). Sensitivity was 60.61% (40/66) and specificity was 100% (40/40). Positive predictive value and negative predictive value were 100% and 62.3%, respectively. Atypical CT pattern was more frequent in COVID-19-negative patients (9 (14%) vs 24 (56%) in COVID-19-positive, p < 0.001), while the indeterminate pattern was similar in both groups (13 (20%) vs 6 (14%), p = 0.606), and negative pattern was more common in COVID-19-negative patients (4 (6%) vs 12 (28%), p = 0.002). In hospitalized ESKD patients on RRT, atypical chest CT pattern cannot adequately rule out the diagnosis of COVID-19.

Temporal Association Between COVID-19 Immunoglobulin-G Antibody Induced Focal Cerebral Arteriopathy and New-Onset Acute Ischemic Stroke in a Pediatric: Is it Causal or Coincidental?

ABSTRACT Focal cerebral arteriopathies, vasculitis, microangiopathies, coagulopathies, and in-situ microthrombi leading to territorial infarction of neural tissues are some of the most recent instances which are reported as a consequence of the infection caused by the novel coronavirus (SARS-CoV-2). Acute ischemic stroke (AIS) is one of the major neurological manifestations that have been linked with COVID-19. We describe a case of a 5-year-old boy who had an acute-onset of bilateral arm and leg weakness due to a posterior circulatory ischemic stroke that was temporally associated with COVID-19 Immunoglobulin-G antibody-induced cerebral arteriopathies and vasculitis. Laboratory examination was suggestive of elevated D-dimer levels to 3302 ng/ml, elevated C-reactive protein to 10 mg/dl, and elevated fibrinogen levels to 433 mg/dl. He had a negative COVID-19 nasopharyngeal polymerase chain reaction and positive COVID-19 serologies. Focal cerebral arteriopathy and AIS were managed by administering early antithrombotics, steroids, and multivitamins. On routine follow-ups, the patient remained free from new neurological and functional deficits. Although many hypotheses are proposed to explain the causal relationship between the two, it could as well be sheer coincidence.

Unraveling the neurological mysteries of COVID-19: A fatal case of pediatric stroke

A 15-year-old girl presents to a local hospital with headache, fever, generalized tonic clonic seizures, blurred vision and loss of consciousness. A brain MRI showing atrophy, ischemic changes and leukomalacia was followed with a positive COVID-19 test that warranted an admission to an isolation center. A presumptive diagnosis of meningeal encephalitis was made and treatment with ceftriaxone and vancomycin was initiated with serial measurements showed low vitals, electrolytes and Glasgow Coma Score daily until her death.

Findings Associated With Prolonged COVID-19 Recovery Among Boston Healthcare Workers.

This study aimed to evaluate the long-term, symptomatic recovery of healthcare workers from acute COVID-19 infections up to 3 years after the initial COVID-19 outbreak. A cross-sectional study was performed among employees of a community-based healthcare system in Massachusetts who had a recorded positive COVID-19 test. Survey responses were collected between September 2022 and January 2023. The survey included validated questionnaires: WHOQOL-BREF, EQ-5D-5 L, DASS-21, FCV-19S, K6+, and the Insomnia Severity Index. We compared the long-COVID (ie, symptoms lasting >28 days) and non-long-COVID groups. Among the 280 respondents (15.2% response rate), those with long COVID (73.4%) reported significantly worse quality of life and greater levels of depression, anxiety, and stress metrics. However, no significant difference was found between the two groups' fear of COVID-19. Targeted support for healthcare workers with prolonged symptoms after COVID-19 is warranted.

Epidemiological Pattern and Case Fatality Rate among COVID-19 Patients during First and Second Wave of Pandemic in Madhesh Province, Nepal

Background &amp; Objectives: Evaluating multi-wave patterns of COVID-19 infection, hospitalization, and mortality across spatial scales can inform public health strategies for future pandemics. However, there is limited understanding of these patterns in developing countries, including Nepal. This study aimed to analyze epidemiological patterns, fatality rates, and factors associated with severe outcomes during the first and second waves of COVID-19 in Madhesh Province, Nepal. Materials and Methods: This retrospective cross-sectional study used provincial health records from Madhesh Province, covering April 9, 2020, to December 15, 2021, to analyze 37,551 positive COVID-19 cases and 1,037 deaths across two waves. The study examined changes in COVID-19-related deaths, with data on demographics, residence, isolation sites, treatment hospitals, care levels, and testing laboratories. The frequency and percentage of the variables were presented. The case fatality rate (CFR) for different categories were calculated. Additionally, the case fatality rate ratio (CFRR) for the first wave against second wave was obtained. Finally, case fatality risk ratios with 95% confidence intervals were presented. A p-value of &lt;0.05 was set as statistically significant. Results: The case fatality rate (CFR) for COVID-19 was significantly higher in the second wave, especially among the elderly (≥47 years), and in institutional isolation (7.82%). Tertiary level care and private hospitals consistently showed higher CFRs. Furthermore, the multivariable analysis of risk ratios (RR) for COVID-19 case fatality in revealed that the 25–34 year age group had the highest RR (2.39). Similarly, males had a higher RR (1.42) than females, and institutional isolation had a substantially higher RR (93.33) compared to home isolation. Primary level care RR (28.11) and government hospitals RR (4.32) showed a higher risk. Place of residence also impacted the RR, with Sarlahi (7.68) having higher. Conclusion: A significant increase in COVID-19 case fatality rates during the second wave, particularly among the elderly and those in institutional isolation. Higher mortality was observed in tertiary hospitals and among those who were tested in private laboratories, with substantial variations in risk ratios based on age, isolation type, and place of residence.

Retrospective Analysis of Omicron in Minas Gerais, Brazil: Emergence, Dissemination, and Diversification.

Brazil is one of the countries most affected by COVID-19, with the highest number of deaths recorded. Brazilian Health Institutions have reported four main peaks of positive COVID-19 cases. The last two waves were characterized by the emergence of the VOC Omicron and its sublineages. This study aimed to conduct a retrospective surveillance study illustrating the emergence, dissemination, and diversification of the VOC Omicron in 15 regional health units (RHUs) in MG, the second most populous state in Brazil, by combining epidemiological and genomic data. A total of 5643 confirmed positive COVID-19 samples were genotyped using the panels TaqMan SARS-CoV-2 Mutation and 4Plex SC2/VOC Bio-Manguinhos to define mutations classifying the BA.1, BA.2, BA.4, and BA.5 sublineages. While sublineages BA.1 and BA.2 were more prevalent during the third wave, BA.4 and BA.5 dominated the fourth wave in the state. Epidemiological and viral genome data suggest that age and vaccination with booster doses were the main factors related to clinical outcomes, reducing the number of deaths, irrespective of the Omicron sublineages. Complete genome sequencing of 253 positive samples confirmed the circulation of the BA.1, BA.2, BA.4, and BA.5 subvariants, and phylogenomic analysis demonstrated that the VOC Omicron was introduced through multiple international events, followed by transmission within the state of MG. In addition to the four subvariants, other lineages have been identified at low frequency, including BQ.1.1 and XAG. This integrative study reinforces that the evolution of Omicron sublineages was the most significant factor driving the highest peaks of positive COVID-19 cases without an increase in more severe cases, prevented by vaccination boosters.

Characterizing the impact of the Covid-19 pandemic on adults with autosomal dominant polycystic kidney disease: a cross-sectional study

BackgroundThe Covid-19 pandemic greatly affected those with chronic diseases, impacting healthcare access and healthcare seeking behaviors. The impact of the pandemic on adults with Autosomal Dominant Polycystic Kidney Disease (ADPKD) has not been investigated.MethodsParticipants were recruited from a cohort of 239 ADPKD patients enrolled in a longitudinal study at the University of Maryland. Patients on renal replacement therapy were excluded. N = 66 patients participated in a phone questionnaire from June 2022-December 2022 about ADPKD-related complications, concern about contracting Covid-19, healthcare-seeking behaviors, and telehealth utilization before and after March 2020.ResultsN = 34 (51.5%) of participants reported a positive Covid-19 test result. N = 29 (44%) expressed high concern of contracting Covid-19. Those who avoided medical care at least once (N = 17, 25.8%) had similar demographics and ADPKD severity to those who did not, but reported greater telehealth utilization (88.2% vs. 42.9%, p = 0.002), greater use of non-prescribed medication for Covid-19 treatment or prevention (35.3% vs. 8.2%, p = 0.01), and were more likely to contract Covid-19 (76.5% vs. 42.9%, p = 0.02). Among the N = 53 who reported very good or excellent ADPKD disease management pre-pandemic, N = 47(89%) reported no significant change during the pandemic.ConclusionsIn this highly educated, high-income cohort with a mean age of 46.1 years, most people reported well-managed ADPKD prior to the pandemic. This may explain why less than half of participants expressed high concern for contracting Covid-19. Overall, there was no significant pandemic-related decline in self-reported ADPKD management. This was likely due to this cohort’s excellent access to, and uptake of, telehealth services. Notably, 1 in 4 participants reported healthcare avoidant behavior, the effect of which may only be seen years from now. Future studies should investigate potential impacts of avoidant behaviors, as well as expand investigation to a more diverse cohort whose care may not have been as easily transitioned to telehealth.

Impulsivity and Its Association with Depression and Anxiety in the Normal Egyptian Population Post COVID-19 Pandemic.

Background and Objectives: It is well known that depression, anxiety, and impulsiveness are interrelated; however, studies that have assessed their association with the coronavirus outbreak are scarce. Hence, our study aimed to evaluate the impulsivity incidence and its correlation with anxiety and depression following COVID-19 infection between November 2022 and June 2023. Materials and Methods: The 201 participants completed the Hamilton Depression Rating Scale (HDRS), Hamilton Anxiety Rating Scale (HAM-A), Sheehan Disability Scale (SDS), and short UPPS-P scales (urgency, premeditation, perseverance, sensation seeking, and positive urgency) to allow us to determine their anxiety and depression symptoms, functional impairment, and impulsivity, respectively. Results: Among our respondents, 22%, and 26.7% had moderate to severe anxiety and depression. The short UPPS-P scale significantly correlated with the HAM-A and HDRS scales. Participants with positive COVID-19 infection showed significantly higher functional impairment scores, especially in the work/study domain (mean (SD): 3.12 (2.2) vs. 2.43 (2.3); p = 0.037). COVID-19-related disruption significantly correlated with negative and positive urgency, HAM-A, HDRS, and the SDS total and subscales. Conclusions: Our findings showed a notable increase in anxiety, depression, and functional impairment among the population following COVID-19 infection. Our research highlights the correlation between impulsivity and the psychological distress experienced following the pandemic.

Community Organizations, Local Health Equity Action Teams, and a Learning Collaborative to Address COVID-19 Disparities in Urban and Rural Communities.

Rapid Acceleration of Diagnostics-Underserved Populations (RADx-UP) Kansas worked with 10 Kansas counties from November 2020 through June 2022 to form local health equity action teams (LHEATs), develop COVID-19 testing strategies, foster communication about COVID-19, and share best practices through a learning collaborative. Participating counties documented 693 distinct COVID-19 testing and 178 communication activities. Although the intervention was not associated with changes in the proportion of positive COVID-19 tests, LHEATs in the learning collaborative implemented new testing strategies and responded to emerging COVID-19 challenges. (Am J Public Health. Published online ahead of print August 22, 2024:e1-e5. https://doi.org/10.2105/AJPH.2024.307771).

Exemplifying successful sports event amidst the pandemic: the case of the Turkish women's football super league

Objective: The aim of this study is to define the COVID-19 positivity rate, transmission routes and clinical symptoms in the group of female football players competing in the Turkish Women's Football Super League, where the bubble protocol was implemented during the full lockdown period when the cases peaked. Material and Methods: A retrospective observational study was carried out to include a total of 557 participants during the Turkish Women's Football Super League 3‐week event (April 17-May 5, 2021). This event was held within the scope of the bubble protocol developed for sports events during the full lockdown period of the pandemic. Regular reverse transcriptase PCR (RT-PCR) screenings were carried out as part of a standard procedure (48-72 hours prior to hotel check-in, upon arrival, and the day before matches) to assess the possible presence of the COVID-19 virus carriage. Results: In the pre-arrival test, COVID-19 was detected in 5.03% of football players (19/377). A positivity rate of 0.27% (1/367) was found in football players at the entrance to the hotel facilities. Of the tests performed to footballers during the "Bubble", COVID-19 has been detected in 0.54% (2/367). Tests of 1 team manager and 2 referees, who were in the "bubble protocol" but not in contact with players, were positive. All 6 detected cases were asymptomatic. 5 cases later showed flu-like symptoms. It was revealed that 5 out of 6 cases had contact with a positive case before the tournament. Conclusion: The bubble protocol, which includes testing, advanced hygiene, social distancing and daily symptom monitoring strategies can minimize the transmission of COVID-19 and provide a safe environment for sports organizations.

Study of Postacute Sequelae of COVID-19 Using Digital Wearables: Protocol for a Prospective Longitudinal Observational Study.

Postacute sequelae of COVID-19 (PASC) remain understudied in nonhospitalized patients. Digital wearables allow for a continuous collection of physiological parameters such as respiratory rate and oxygen saturation that have been predictive of disease trajectories in hospitalized patients. This protocol outlines the design and procedures of a prospective, longitudinal, observational study of PASC that aims to identify wearables-collected physiological parameters that are associated with PASC in patients with a positive diagnosis. This is a single-arm, prospective, observational study of a cohort of 550 patients, aged 18 to 65 years, male or female, who own a smartphone or a tablet that meets predetermined Bluetooth version and operating system requirements, speak English, and provide documentation of a positive COVID-19 test issued by a health care professional within 5 days before enrollment. The primary end point is long COVID-19, defined as ≥1 symptom at 3 weeks beyond the first symptom onset or positive diagnosis, whichever comes first. The secondary end point is chronic COVID-19, defined as ≥1 symptom at 12 weeks beyond the first symptom onset or positive diagnosis. Participants must be willing and able to consent to participate in the study and adhere to study procedures for 6 months. The first patient was enrolled in October 2021. The estimated year for publishing the study results is 2025. This is a fully decentralized study investigating PASC using wearable devices to collect physiological parameters and patient-reported outcomes. The study will shed light on the duration and symptom manifestation of PASC in nonhospitalized patient subgroups and is an exemplar of the use of wearables as population-level monitoring health tools for communicable diseases. ClinicalTrials.gov NCT04927442; https://clinicaltrials.gov/study/NCT04927442. DERR1-10.2196/57382.

Automated Immunoprecipitation, Sample Preparation, and Individual Ion Mass Spectrometry Platform for Proteoforms.

Charge detection mass spectrometry (CDMS) is a well-established technique that provides direct mass spectral outputs regardless of analyte heterogeneity or molecular weight. Over the past few years, it has been demonstrated that CDMS can be multiplexed on Orbitrap analyzers utilizing an integrated approach termed individual ion mass spectrometry (I2MS). To further increase adaptability, robustness, and throughput of this technique, here, we present a method that utilizes numerous integrated equipment components including a Kingfisher system, SampleStream platform, and Q Exactive mass spectrometer to provide a fully automated workflow for immunoprecipitation, sample preparation, injection, and subsequent I2MS acquisition. This automated workflow has been applied to a cohort of 58 test subjects to determine individualized patient antibody responses to SARS-CoV-2 antigens. Results from a range of serum donors include 37 subject I2MS spectra that contained a positive COVID-19 antibody response and 21 I2MS spectra that contained a negative COVID-19 antibody response. This high-throughput automated I2MS workflow can currently process over 100 samples per week and is general for making immunoprecipitation-MS workflows achieve proteoform resolution.

Risk factors for long COVID syndrome in postmenopausal women with previously reported diagnosis of COVID-19

PurposeLong COVID-19 syndrome occurs in 10–20 % of people after a confirmed/probable SARS-COV-2 infection; new symptoms begin within three months of COVID-19 diagnosis and last > 8 weeks. Little is known about risk factors for long COVID, particularly in older people who are at greater risk of COVID complications. MethodsData are from Women’s Health Initiative (WHI) postmenopausal women who completed COVID surveys that included questions on whether they had ever been diagnosed with COVID and length and nature of symptoms. Long COVID was classified using standard consensus criteria. Using WHI demographic and health data collected at study enrollment (1993–98) through the present day, machine learning identified the top 20 risk factors for long COVID. These variables were tested in logistic regression models. ResultsOf n = 37,280 survey respondents, 1237 (mean age = 83 years) reported a positive COVID-19 test and 425 (30 %) reported long COVID. Symptoms included an array of neurological, cardio-pulmonary, musculoskeletal, and general fatigue, and malaise symptoms. Long COVID risk factors included weight loss, physical and mobility limitations, and specific heath conditions (e.g., history of heart valve procedure, rheumatoid arthritis). ConclusionsKnowledge of risk factors for long COVID may be the first step in understanding the etiology of this complex disease.

Long-term trends in cycle threshold values: a comprehensive analysis of COVID-19 dynamics, viral load, and reproduction number in South Korea.

With the emergence of COVID-19 cases, governments quickly responded with aggressive testing, contact tracing, isolation and quarantine measures. South Korea's testing strategy primarily relied on real-time reverse-transcriptase polymerase chain reaction (real-time RT-PCR), focusing on cycle threshold (Ct) values, indicative of viral load, to determine COVID-19 positivity. This study examined the long-term time series distribution of Ct values measured in the same laboratory using a nationally standardized testing type and sampling method in South Korea. It aimed to link Ct values, new COVID-19 cases, and the reproduction number (Rt), setting the stage for using Ct values effectively. This study analyzed nationally collected 296,347 samples Ct values from February 2020 to January 2022 and examined their associations with the number of new cases and Rt trends. The data were categorized into four COVID-19 periods for in-depth analysis. Statistical methods included time series trend analysis, local regression for smoothing, linear regression for association analysis, and calculation of correlation coefficients. The median Ct values across four COVID-19 periods decreased gradually from 31.71 in the initial period to 21.27 in the fourth period, indicating higher viral load. The comparison of trends between Ct values and the number of new cases revealed that the decline in Ct values preceded the surge in new cases, particularly evident during the initial stages when new cases did not undergo a significant increase. Also, during variant emergence and vaccination rollout, marked shifts in Ct values were observed. Results from linear regression analysis revealed a significant negative relationship between Ct values and new cases (β = -0.33, p < 0.001, R 2 = 0.67). This implies that as Ct values decrease, new case numbers increase. This study demonstrates the potential of Ct values as early indicators for predicting confirmed COVID-19 cases during the initial stages of the epidemic and suggests their relevance in large-scale epidemic monitoring, even when case numbers are similar.

Assessment of the hematologic factors as a prognostic factor in COVID-19 patients

Introduction: Identifying laboratory predictors of disease progression should be a priority in current COVID-19 studies, which leads to an appropriate treatment for patients and reduce the risk of severe or critical illness. In this study we tend to analyze the hematologic and biochemical findings of COVID-19 patients as an easy-to-get diagnostic factor that can become the first choice for disease monitoring and the evaluation of general conditions. Methods: In this retrospective study, all patients with positive COVID-19 diagnosis that admitted to the emergency department, from 1st of April 2020, to 30th June, 2020 were included. For all patients, CBC, differential, urea, serum creatinine, and CRP were collected. Data analysis was performed using IBM® SPSS® Statistics 19.0 software. Pearson correlation and spearman correlation were used to analyze quantitative and qualitative data correlations respectively. Diagnostic ability of the variables was identified by their ROC curves. Results: A total number of 977 patients were included in this study. The median and mode of the age of the population are 50 and 29 respectively. ROC curves for diagnostic ability indicated that, Urea and creatinine have the highest diagnostic values with its optimum sensitivity and specificity for urea=62.5 mg/dL and creatinine=2.05 mg/dL, with sensitivities of 87.5% and 81.3%, and specificities of 80.6% and 82.1% respectively. Conclusion: The results from the current study show that no chemical or hematologic factor can properly detect COVID-19 in patients. Also, hematologic factors cannot determine patients’ prognosis; however creatinine and urea are able to estimate patients’ prognosis. Therefore, it is recommended to focus on the kidney injuries in COVID-10 patients for predicting their prognosis.

Admission blood tests predicting survival of SARS-CoV-2 infected patients: a practical implementation of graph convolution network in imbalance dataset

BackgroundPredicting an individual’s risk of death from COVID-19 is essential for planning and optimising resources. However, since the real-world mortality rate is relatively low, particularly in places like Hong Kong, this makes building an accurate prediction model difficult due to the imbalanced nature of the dataset. This study introduces an innovative application of graph convolutional networks (GCNs) to predict COVID-19 patient survival using a highly imbalanced dataset. Unlike traditional models, GCNs leverage structural relationships within the data, enhancing predictive accuracy and robustness. By integrating demographic and laboratory data into a GCN framework, our approach addresses class imbalance and demonstrates significant improvements in prediction accuracy.MethodsThe cohort included all consecutive positive COVID-19 patients fulfilling study criteria admitted to 42 public hospitals in Hong Kong between January 23 and December 31, 2020 (n = 7,606). We proposed the population-based graph convolutional neural network (GCN) model which took blood test results, age and sex as inputs to predict the survival outcomes. Furthermore, we compared our proposed model to the Cox Proportional Hazard (CPH) model, conventional machine learning models, and oversampling machine learning models. Additionally, a subgroup analysis was performed on the test set in order to acquire a deeper understanding of the relationship between each patient node and its neighbours, revealing possible underlying causes of the inaccurate predictions.ResultsThe GCN model was the top-performing model, with an AUC of 0.944, considerably outperforming all other models (p < 0.05), including the oversampled CPH model (0.708), linear regression (0.877), Linear Discriminant Analysis (0.860), K-nearest neighbours (0.834), Gaussian predictor (0.745) and support vector machine (0.847). With Kaplan-Meier estimates, the GCN model demonstrated good discriminability between low- and high-risk individuals (p < 0.0001). Based on subanalysis using the weighted-in score, although the GCN model was able to discriminate well between different predicted groups, the separation was inadequate between false negative (FN) and true negative (TN) groups.ConclusionThe GCN model considerably outperformed all other machine learning methods and baseline CPH models. Thus, when applied to this imbalanced COVID survival dataset, adopting a population graph representation may be an approach to achieving good prediction.